## Confidential Client

Data communication system for a confidential medical product. The data rendered involved a complex set of variables and performs predictive statistics, based on live and historical measurement.

This is an analog prototype of how such a system would behave when fed live data.

## Starting point

Step 1

## Possible Premises

## Mapping Axis

## Drawing Logic

## Next Steps:

## Reiterating the approach

Step 2

## Assumptions

This is an analog prototype of how such a system would behave when fed live data.

## Starting point

- page for each subject
- graph for each metric, based on time
- same visual representation for each metric
- vertical slicing by timestamp

## Opportunities

- overlaying metrics to understand anomalies
- drawing cross–subject conclusions
- looking beyond event–specific peaks in metrics

Step 1

## Initial Ideas

- moving away from time based, 2D graphs
- experimenting with overlapping cards
- developing the concept of a data card, and the subsequent
*user “signature”*

## Possible Premises

- each point in time, for each subject, for each metric gets a card
- cards can be thematically linked
- each metric gets a shape assigned to it, depending on the number of variables it constitutes
- a collection of linked cards could be a subject’s signature

**Graphic representation of thematically grouped graphs:**- 2 vars : 2 lines, normal graph
- 3 vars : triangle
- 4 vars : rectangle
- results can be a point, line or an area (shape)

## Mapping Axis

- can we simplify our graph schemas and collate similar metrics?
- our unique timestamp approach (for each card) creates an opportunity for simpler visuals

## Drawing Logic

- points are drawn at the intersection of axis, or with the edge of the shape, whatever is first
- even in a triangle the results could be rendered as a shape if there is no intersection point
- calculating intersection points is done from top to bottom
- an axis can only be used once to render a point

## Next Steps:

- choose an option for our graph schema
- decide on the fidelity of spectrum analysis
- consider noise within the realistic range
- prototype a full signature for a positive, noisy and negative states

## Reiterating the approach

- We’re listening to our subject’s metrics based on realistic values and their signature
- we don’t know what we’re looking for, nor when will it come
- we know that a negative reaction will be multi–dimensional and “loud”
- that allows us to focus on core ranges, and listen to large anomalies

Step 2

## Assumptions

- Each timestamp gets a data card
**time moves in the z axis**- a collection of overlapped cards makes the user signature for that timestamp

## Rules

- starts at 12 o'clock
- moves clockwise
- when lines meet they create an orange dot, and their line disappear
- orphan lines create a dot when they hit the bounding box
- 2 dots create a line, 3 a triangle and so forth

Initial Sketches

*Further Refinements*

*A mock-up made with*

stationary data

stationary data